title: Integration, warehousing, and analysis strategies of Omics data.
abstract: "-Omics" is a current suffix for numerous types of large-scale biological data generation procedures, which naturally demand the development of novel algorithms for data storage and analysis. With next generation genome sequencing burgeoning, it is pivotal to decipher a coding site on the genome, a gene's function, and information on transcripts next to the pure availability of sequence information. To explore a genome and downstream molecular processes, we need umpteen results at the various levels of cellular organization by utilizing different experimental designs, data analysis strategies and methodologies. Here comes the need for controlled vocabularies and data integration to annotate, store, and update the flow of experimental data. This chapter explores key methodologies to merge Omics data by semantic data carriers, discusses controlled vocabularies as eXtensible Markup Languages (XML), and provides practical guidance, databases, and software links supporting the integration of Omics data.
authors.affiliation: Stanford University School of Medicine, Stanford, CA, USA. gedela@stanford.edu
authors.forename: Srinubabu
authors.initials: S
authors.lastname: Gedela
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D030562:Databases, Protein; D006801:Humans; D019451:Information Management / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D008954:Models, Biological; D012984:Software